What Is XDR (Extended Detection and Response)?

How XDR Security Works

An XDR system continuously captures data and alerts from multiple connected security systems and IT environments, and feeds the data into a centralized data lake for cleaning and normalization.

Like EDR, XDR can deploy agents on employee workstations, mobile devices, IoT, and an ever-growing variety of endpoints. However, it also leverages data feeds from email security systems, network analysis and visualization tools, identity and access management platforms, and cloud workload protection platforms.

With these varied, integrated datasets, XDR systems go beyond traditional correlation, applying advanced machine learning to identify new threats across diverse infrastructure while reducing false positives.

Most important, XDR alerts are highly actionable. Many of them lead to automated responses performed by the XDR system, directing connected systems such as endpoint security and email gateways to perform specific tasks without human intervention. Other, more complex recommendations, are displayed visually for analysts, allowing them to investigate and respond to the threat from a single console without having to switch tools.

Related content: Read our guide to XDR security

EDR Versus MDR Versus XDR: What is the Difference?

Endpoint Detection and Response (EDR) is an endpoint-based monitoring and threat detection tool that is considered essential in modern cybersecurity toolsets. The solution relies on software agents or sensors installed on endpoints to capture data, send it to a central repository for analysis, and enable analysts to investigate and respond to breaches on endpoint devices.

Managed Detection and Response (MDR) is essentially EDR provided as a service. The service focuses on managing the security of endpoints and mitigating, eliminating, and remediating threats by experienced and professional security teams. It typically includes, together with the managed service, an EDR software solution.

XDR extends EDR capabilities to provide protection beyond endpoints. XDR solutions collect data from across the infrastructure, simplifying analysis and security workflows across security stack. They increase visibility and unify response to advanced hidden threats, which cannot be addressed by EDR or MDR alone. When purchased as a managed solution, XDR also provides access to experienced threat hunting, threat intelligence and analytics experts, similar to MDR services.

Related content: Read our guide to:

• EDR vs. XDR

• MDR vs. XDR

Open XDR vs. Native XDR

There are two primary XDR architectures: open XDR and native XDR.

Open XDR

Open XDR vendors offer solutions focused mainly on the workflow engine and back-end analytics. Some open XDR vendors also offer prescriptive content across the full lifecycle of threat detection, investigation, and response (TDIR) to provide out-of-the-box solutions for common SOC use cases.

XDR solutions often serve as a single control plane that centralizes several products and vendors. Open XDR solutions can integrate with existing security tools and IT infrastructure. Once integrated, open XDR solutions can correlate and analyze data to automate and optimize your TDIR workflows. The goal is to provide the visibility, orchestration, and automation capabilities needed to facilitate rapid response to incidents.

Native XDR

A native XDR is a closed ecosystem that includes:

• Front-end solutions that generate data

• Back-end capabilities that provide analysis and workflows

Native XDR solutions provide all sensors needed for common XDR use cases, such as endpoints, the network level, cloud environments, identity protection, and email accounts. The solution uses this data to perform threat detection, investigation, and response. More advanced capabilities include additional sensors to extend visibility and efficient advanced analytics.

SOC Challenges and How XDR Can Address Them

The Security Operations Center (SOC) is responsible for detecting and responding to security threats. SOC analysts need to quickly identify critical threats to minimize the organization's security risks. Here is how XDR can support challenges that arise in this process:

Alert Overload

Alerts from SIEM systems can overwhelm security teams. For a company with 1,000 employees, the number alerts can be as high as two million per day. No matter how skilled the analysts, it is impossible to manually evaluate and prioritize such a large number of events.

XDR helps reduce noise by combining multiple events into one, organized according to the kill chain. It also eliminates most low priority or false positive alerts. This dramatically reduces the number of alerts and improves their quality and actionability.

Gaps in Visibility

Different security products provide different forms of visibility that prioritize different needs. Different products can be combined to integrate and correlate security data, but the depth of the data and the limitations of individual products can create visibility gaps.

XDR collects activity data from multiple security tools and combines it into a data lake. It uses advanced analytics to provide a complete picture of the chain of security events across multiple security layers, providing improved visibility.

Challenges of Conducting Investigations

When analysts need to wade through logs and alerts without clear metrics, it can be difficult to identify meaningful patterns, threat paths, and impacts. The research required to extract security insights from data takes time, effort and resources.

XDR automates investigations and eliminates the need for manual processes, providing analytical tools and access to vast amounts of high-quality data. For example, root cause analysis can be automated so that security analysts can immediately see attack vectors and timelines in the XDR alert, and zoom in on individual elements of the attack chain that interest them.

Slow Detection and Response Times

In a traditional SOC process, many threats remain undetected, increasing the risk of successful breaches and limiting the ability of security teams to respond in a timely manner. This increases response time and thus the risk and damage of cyberattacks. This impacts key performance indicators of the SOC, such as mean time to respond (MTTR) and mean time to discovery (MTTD).

XDR increases threat detection rates, reduces response times, minimizing MTTR, MTTD, and related metrics. This can improve the overall effectiveness of the SOC and minimize business risk.

Requirements for XDR Solutions in the Enterprise

Here are several requirements to consider when implementing XDR:

Unified Telemetry

Traditional security tools focus on a single point of attack on a network element or surface. XDR, on the other hand, spans a broader lifecycle, including endpoint detection and response (EDR) solutions, endpoint protection platforms (EPP), email and web gateways, and identity and access management (IAM).

XDR helps provide consistent telemetry across all systems in a complex environment, including cloud infrastructure, SaaS applications, and on-premise resources. It centralizes visibility to help rapidly investigate threats.

Cloud-Native Architecture

Ideally, XDR solutions should incorporate a cloud native architecture that supports scalable storage and flexible deployment on various infrastructure types. You do not need to deploy XDR on the public cloud for the solution to be cloud native. Rather, these solutions can support on-premises or hybrid deployments while using cloud native principles to maintain agility and scalability.

Proactive Analysis

XDR platforms should be able to act autonomously and take proactive steps to discover attacks as they occur. It typically involves using machine learning analysis to identify indicators of attacker activity before actors can penetrate critical systems or cause damage.

XDR platforms can leverage historical data from the organization, other clients, and threat intelligence feeds to detect unknown and new variations of known threats. Ideally, XDR platforms should expand their portfolio of attack stories continuously and compare these stories to security events. It can help reduce false positives and surface real threats.

Improving Alert Quality

XDR platforms go beyond pushing log data or forwarding alerts. These platforms collect data, validate its significance, and surface important signals that can contribute to understanding the attack story. It helps security analysts detect real attacks and provides the information needed for quick remediation.

XDR can supplement, replace, or complement SIEM and SOAR tools. It helps incorporate various inputs and feed them into behavioral analysis to provide effective detection and response. It is particularly helpful for detecting and assessing targeted attacks.

How to Evaluate XDR Platforms

XDR platforms typically use similar architectures and processes but can differ greatly in other aspects, including:

Data Sources

XDR platforms rely on data, but each platform may collect data from sources at different levels. For example, some XDR platforms rely on endpoint detection data, while others collect data traversing the network. Depending on your use case, you may need to collect data from specific endpoints or the entire network.

Use Case Requirements

Each organization has its own unique requirements. Ideally, the XDR solution you choose should meet your unique requirements. Here are key considerations:

• Users — when assessing a solution, you should consider your users and their location — what is the extent of geographical distribution?

• Location — you should also determine the location of data, applications, and servers — are these resources located in the cloud or on-premises?

• Sensitivity level—it is critical to protect sensitive data with the appropriate measures, especially if sensitive data is traversing untrustworthy networks like the Internet.

Consider each of the above factors and choose the solution that enables you to meet your unique requirements.

Threat Intelligence and Hunting

Most XDR platforms provide threat intelligence and hunting capabilities. However, the scope of the data and the extent of hunting can differ greatly, and some may not be as proactive as others. Enterprise-grade XDR typically employs in-house threat detection teams to identify emerging and new threats.

XDR teams work to identify threats rapidly and create a policy to help protect against zero-day exploits. These teams gather threat intelligence information from various sources, including sources external to the protected organization. This information helps the team automatically create security policies and push them to customer security tools.

Artificial intelligence (AI)

Most XDR platforms employ AI, offering a range of capabilities. For example, some platforms employ AI to identify threats and reduce false positives. In contrast, others use AI to perform root cause analysis and provide remediation guidance to minimize threat investigation, containment, and elimination time.

Storage and Bandwidth

When considering an XDR solution, you should determine the amount of log and telemetry data you need to collect and the appropriate storage retention time for this data. This information can help you define storage space requirements for the XDR platform and the predicted bandwidth consumption across WANs, LANs, and cloud connections when sending data to XDR data collection agents.

Deployment Approaches

You can approach deployment in two main ways:

• Deploy XDR data collection services across all servers, clouds, and endpoints.

• Implement a phased rollout approach and start with a subset of the above categories.

A phased rollout approach can help you learn the platform in detail before rolling out to other network and device types. It helps ensure the rollout does not affect business operations accidentally.